Mendelian Randomization (Using genes to tell us about the environment) David Evans University of Queensland University of Bristol

RCTs are the Gold Standard in Inferring Causality RANDOMISED CONTROLLED TRIAL RANDOMISATION METHOD EXPOSED: INTERVENTION CONTROL: NO INTERVENTION CONFOUNDERS EQUAL BETWEEN GROUPS OUTCOMES COMPARED BETWEEN GROUPS

Observational Studies RCTs are expensive and not always ethical or practically feasible Association between environmental exposures and disease can be assessed by observational epidemiological studies like case-control studies or cohort studies The interpretation of these studies in terms of causality is problematic

CHD risk according to duration of current Vitamin E supplement use compared to no use RR Rimm et al NEJM 1993; 328: 1450-6

Use of vitamin supplements by US adults, 1987-2000 Percent Source: Millen AE, Journal of American Dietetic Assoc 2004;104:942-950

Vitamin E levels and risk factors: Women’s Heart Health Study Childhood SES Manual social class No car access State pension only Smoker Daily alcohol Exercise Low fat diet Obese Height Leg length Lawlor et al, Lancet 2004

Vitamin E supplement use and risk of Coronary Heart Disease 1.0 Stampfer et al NEJM 1993; 328: 144-9; Rimm et al NEJM 1993; 328: 1450-6; Eidelman et al Arch Intern Med 2004; 164:1552-6

“Well, so much for antioxidants.”

Classic limitations to “observational” science Confounding Reverse Causation Bias

An Alternative to RCTs: Mendelian randomization In genetic association studies the laws of Mendelian genetics imply that comparison of groups of individuals defined by genotype should only differ with respect to the locus under study (and closely related loci in linkage disequilibrium with the locus under study)   Genotypes can proxy for some modifiable risk factors, and there should be no confounding of genotype by behavioural, socioeconomic or physiological factors (excepting those influenced by alleles at closely proximate loci or due to population stratification) Mendel in 1862

Fisher and Confounding “Generally speaking the geneticist, even if he foolishly wanted to, could not introduce systematic errors into comparison of genotypes, because for most of the relevant time he has not yet recognized them” Fisher (1952)

Mendelian randomisation and RCTs RANDOMISED CONTROLLED TRIAL RANDOM SEGREGATION OF ALLELES RANDOMISATION METHOD EXPOSED: FUNCTIONAL ALLELLES CONTROL: NULL ALLELLES EXPOSED: INTERVENTION CONTROL: NO INTERVENTION CONFOUNDERS EQUAL BETWEEN GROUPS CONFOUNDERS EQUAL BETWEEN GROUPS OUTCOMES COMPARED BETWEEN GROUPS OUTCOMES COMPARED BETWEEN GROUPS

Mendelian Randomization- Core Assumptions Confounders SNP Exposure Outcome (1) SNP is associated with the exposure (2) SNP is not associated with confounding variables (3) SNP only associated with outcome through the exposure

Equivalence Between Directed Acyclic Graphs and SEMs Confounders SNP Exposure Outcome ξ1 ξ2 SNP Exposure Outcome βx βY

Why Perform MR? Assess causal relationship between two variables Estimate magnitude of causal effect

Calculating Causal Effect Estimates Confounders SNP Exposure Outcome βSNP-EXPOSURE βEXP-OUTCOME βSNP-OUTCOME 2SLS: (1) Regress exposure on SNP (2) Regress outcome on predicted exposure from 1st stage regression (3) Adjust standard errors Wald Test: βSNP-OUTCOME / βSNP-EXPOSURE *Can be used in different samples (“Two sample MR”)

Calculating the Causal Effect via SEM Confounders SNP Exposure Outcome ξ1 ξ2 SNP Exposure Outcome βx βY

Limitations to Mendelian Randomisation 1- Pleiotropy 2- Population stratification 3- Canalisation 4- Power (also “weak instrument bias”) 5- The existence of instruments

MR References